infile3<-"mean_day244_rescaled.rst"          #This image serves as the reference grid for kriging

infile4<- "orcnty24_OR83M.shp"               #Vector file defining the study area: Oregon state and its counties.

prop<-0.3                                    #Propotion of weather stations retained for validation/testing

###STEP 1 DATA PREPARATION AND PROCESSING#####

for(i in 1:length(dates)){            # start of the for loop #1

#i<-3                                           #Date 10 is used to test kriging

  n<-nrow(ghcn.subsets[[i]])

  ns<-n-round(n*prop)                             #Create a sample from the data frame with 70% of the rows

  nv<-n-ns                                        #create a sample for validation with prop of the rows

  #Cokriging tmax

  g<-gstat(NULL,"tmax", tmax~1, data_s)                   #This creates a gstat object "g" that acts as container for kriging specifications.

  g<-gstat(g, "SRTM_elev",ELEV_SRTM~1,data_s)            #Adding variables to gstat object g

  vm_g<-variogram(g)                                     #Visualizing multivariate sample variogram.

  vm_g.fit<-fit.lmc(vm_g,g,vgm(2000,"Sph", 100000,1000)) #Fitting variogram for all variables at once.

# Now turn it into a data.frame...

results_table<-as.data.frame(results_num)